Read chromatography and mass spectrometry binary files
Project description
rainbow
rainbow provides programmatic access to the raw data encoded in chromatography and mass spectrometry binary files. This library supports the following vendors and detectors:
Agilent .D
.uv- UV spectrum (supports incomplete files).ch- UV, FID, CAD, and ELSD channels.ms- MS (supports incomplete files)MSProfile.bin- HRMS
Agilent .dx (OpenLab CDS)
.UV- DAD spectrum.CH- single-wavelength UV/DAD signals.IT- instrument telemetry, as analog data (parse withtelemetry=True)
Waters .raw
CHRO- CAD and ELSD, as well as miscellaneous analog dataFUNC- UV and MS
There is documentation for rainbow that also details the structure of each binary file format.
Installation
pip install rainbow-api
Prebuilt wheels include an optional compiled accelerator (see Performance); installation never requires a compiler, and rainbow works the same with or without it.
Usage
The easiest way to get started is to give rainbow a directory path. Assume that we have a directory mydata.D that contains a binary file DAD1.uv with UV data.
import rainbow as rb
datadir = rb.read("mydata.D")
datafile = datadir.get_file("DAD1A.uv")
Here, the datadir DataDirectory object contains a DataFile object for DAD1A.uv.
The raw UV data is contained in numpy arrays that are attributes of datafile. Users may find the following particularly useful:
datafile.xlabels- 1D numpy array with retention timesdatafile.ylabels- 1D numpy array with wavelengthsdatafile.data- 2D numpy array with absorbances
There is a tutorial available. There are also example snippets for basic tasks. Or just check out the full API.
Performance
Decoding Agilent diode-array (DAD) .uv files is the one hot spot in the
library: each file holds a large retention-time × wavelength grid of
delta-encoded absorbances, and the decoding is inherently sequential, so it
cannot be vectorized with NumPy. rainbow ships an optional compiled extension
(rainbow/agilent/_uvdelta.pyx, built with Cython) that runs this inner loop in
C, decoding large DAD files roughly 100× faster while producing
bit-identical results.
The accelerator is entirely optional:
- Prebuilt wheels on PyPI already include it, so
pip install rainbow-apigives you the fast path with no compiler needed. - If you install from source without a compiler (or without Cython), the build
simply skips the extension and rainbow falls back to a pure-Python decoder
with identical output. You can check which path is active with
rainbow.agilent.chemstation._uvdelta_fast is not None.
Other formats (.ch channels, .ms, MassHunter) are already fast and do not
use the accelerator.
Contents
rainbow/contains the code of the Python library.docs/contains code for generating documentation. To build documentation locally, you will need to install thesphinxandsphinx-rtd-themepackages. Then, move to thedocs/directory and runmake html. The docpages will be generated underdocs/_build.tests/contains unit tests for the library. These can be run withpython -m unittest.
For development, an editable install (pip install -e .) compiles the optional
accelerator in place if a C compiler and Cython are available; otherwise the
pure-Python fallback is used. The parity between the two paths is checked by
tests/test_accelerator.py.
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